Digital Segmentation of Priority Populations in Public Health.
William Douglas EvansChristopher N ThomasDionisios FavatasJoseph SmyserJodie BriggsPublished in: Health education & behavior : the official publication of the Society for Public Health Education (2020)
The rapid growth and diffusion of digital media technologies has changed the landscape of market segmentation in the last two decades, including its use in promoting prosocial and behavior change. New, population-specific and culturally appropriate prevention strategies can leverage the potential of digital media to influence health outcomes, especially for the greatest users of digital technology, including youth and young adults. Health behavior change campaigns are increasingly shifting resources to social media, creating opportunities for innovative interventions and new research methods. This article examines three case studies of digital segmentation: (1) tobacco control from the Truth Initiative, (2) community-based public health programs from the Centers for Disease Control and Prevention, and (3) substance use (including opioids) and other risk behavior prevention from Public Good Projects. These case studies of recent digital segmentation efforts in the not-for-profit, government, and academic sectors show that it increases reach and frequency of messages delivered to priority populations. The practice of digital segmentation is rapidly growing, shows early signs of effectiveness, and may enhance future public health campaigns. Additional research could optimize its use and effectiveness in promoting prosocial and behavior change campaign outcomes.
Keyphrases
- public health
- social media
- deep learning
- convolutional neural network
- young adults
- healthcare
- randomized controlled trial
- quality improvement
- primary care
- type diabetes
- health information
- global health
- emergency department
- metabolic syndrome
- machine learning
- adipose tissue
- risk assessment
- pain management
- electronic health record
- single cell
- current status
- skeletal muscle